793 resultados para personalized medecine


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Cardiovascular disease (CVD) is responsible for significant morbidity and mortality in the Western and developing world. This multifactorial disease is influenced by many environmental and genetic factors. At present, public health advice involves prescribed population-based recommendations, which have been largely unsuccessful in reducing CVD risk. This is, in part, due to individual variability in response to dietary manipulations, that arises from nutrient-gene interactions (defined by the term 'nutrigenetics'). The shift towards personalized nutritional advice is a very attractive proposition, where, in principle, an individual can be given dietary advice specifically tailored to their genotype. However, the evidence-base for the impact of interactions between nutrients and fixed genetic variants on biomarkers of CVD risk is still very limited. This paper reviews the evidence for interactions between dietary fat and two common polymorphisms in the apolipoprotein E and peroxisome proliferator-activated receptor-gamma genes. Although an increased understanding of how these and other genes influence response to nutrients should facilitate the progression of personalized nutrition, the ethical issues surrounding its routine use need careful consideration.

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Clinical pathways are widely adopted by many large hospitals around the world in order to provide high-quality patient treatment and reduce the length and cost of hospital stay. However, nowadays most of them are static and nonpersonalized. Our objective is to capture and represent clinical pathway using organizational semiotics method including Semantic Analysis which determines semantic units in clinical pathway, their relationship and their patterns of behavior, and Norm Analysis which extracts and specifies the norms that establish how and when these medical behaviors will occur. Finally, we propose a method to develop clinical pathway ontology based on the results of Semantic Analysis and Norm analysis. This approach will give a contribution to design personalized clinical pathway by defining a set of possible patterns of behavior and theClinical pathways are widely adopted by many large hospitals around the world in order to provide high-quality patient treatment and reduce the length and cost of hospital stay. However, nowadays most of them are static and nonpersonalized. Our objective is to capture and represent clinical pathway using organizational semiotics method including Semantic Analysis which determines semantic units in clinical pathway, their relationship and their patterns of behavior, and Norm Analysis which extracts and specifies the norms that establish how and when these medical behaviors will occur. Finally, we propose a method to develop clinical pathway ontology based on the results of Semantic Analysis and Norm analysis. This approach will give a contribution to design personalized clinical pathway by defining a set of possible patterns of behavior and the norms that govern the behavior based on patient’s condition.

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Knowledge recommendation has become a promising method in supporting the clinicians decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users requirements accurately and realize personalized recommendation. Therefore this paper proposes an ontological approach based on semiotic principles to personalized medical knowledge recommendations. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthermore, the personalized recommendation mechanism is illustrated.

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Knowledge management has become a promising method in supporting the clinicians′ decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users′ requirements accurately and realize personalized matching. Therefore this paper proposes an ontological approach based on semiotic principles to personalized medical knowledge matching. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthmore, the personalized matching mechanism and algorithm are illustrated.

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Stimulation protocols for medical devices should be rationally designed. For episodic migraine with aura we outline model-based design strategies toward preventive and acute therapies using stereotactic cortical neuromodulation. To this end, we regard a localized spreading depression (SD) wave segment as a central element in migraine pathophysiology. To describe nucleation and propagation features of the SD wave segment, we define the new concepts of cortical hot spots and labyrinths, respectively. In particular, we firstly focus exclusively on curvature-induced dynamical properties by studying a generic reaction-diffusion model of SD on the folded cortical surface. This surface is described with increasing level of details, including finally personalized simulations using patient's magnetic resonance imaging (MRI) scanner readings. At this stage, the only relevant factor that can modulate nucleation and propagation paths is the Gaussian curvature, which has the advantage of being rather readily accessible by MRI. We conclude with discussing further anatomical factors, such as areal, laminar, and cellular heterogeneity, that in addition to and in relation to Gaussian curvature determine the generalized concept of cortical hot spots and labyrinths as target structures for neuromodulation. Our numerical simulations suggest that these target structures are like fingerprints, they are individual features of each migraine sufferer. The goal in the future will be to provide individualized neural tissue simulations. These simulations should predict the clinical data and therefore can also serve as a test bed for exploring stereotactic cortical neuromodulation.

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Purpose Personalised intervention may have greater potential for reducing the global burden of non-communicable diseases and for promoting better health and wellbeing across the life-span than the conventional “one size fits all” approach. However, the characteristics of individuals interested in personalised nutrition (PN) are unclear. Therefore, the aim of this study was to describe the characteristics of European adults interested in taking part in an internet-based PN study. Methods Individuals from seven European countries (UK, Ireland, Germany, the Netherlands, Spain, Greece and Poland) were invited to participate in the study via the Food4Me website (http://www.food4me.org). Two screening questionnaires were used to collect data on socio-demographic, anthropometric and health characteristics as well as dietary intakes. Results A total of 5662 individuals expressed an interest in the study (mean age 40 ± 12.7; range 15-87 years). Of these 64.6% were female and 96.9% were Caucasian. Overall, 12.9% were smokers and 46.8% reported the presence of a clinically diagnosed disease. Furthermore, 46.9% were overweight or obese and 34.9% were sedentary during leisure time. Assessment of dietary intakes showed that 54.3% of individuals reported consuming at least 5 portions of fruit and vegetables per day, 45.9% consumed more than 3 servings of wholegrains and 37.2% limited their salt intake to less than 5.75g per day. Conclusions Our data indicate that individuals volunteering to participate in an internet-based PN study are broadly representative of the European adult population, most of whom had adequate nutrient intakes but who could benefit from improved dietary choices and greater physical activity. Future use of internet-based PN approaches is thus relevant to a wide target audience.